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Workbook 2025

Assignments

  • Week 1.1
    • Programming Assignment 1.1: Catch them all
      • Show hidden files
      • Install TU Delft conda
      • Install VS Code
      • Setup mude-base environment
      • Execute python code in VS code in your mude-base environment.
      • GitHub account and Student Developer Pack
    • Workshop 1.1: Warming Up
      • Python exercise
    • Group assignment 1.1: Ice Ice Baby
      • Model comparison
      • Report
  • Week 1.2
    • Programming assignment 1.2: Markdown Mania & Array Artistry
      • Upload files to GitHub and check for pass
      • Report in a markdown file
      • Markdown in a Jupyter notebook file
      • Visualizing a Matrix
      • Creating subplots
      • List comprehension
      • Filling a matrix
      • Programming fundamental concepts: flow
    • Workshop 1.2: Gumbel and Shake
      • Numerical integration and differentiation
    • Group assignment 1.2: Streams & series
      • Part 1: Discharge Estimation and Numerical Integration
      • Part 2: Taylor Series Approximation
      • Part 3: Deriving numerical derivatives from Taylor series expansions
      • Report
  • Week 1.3
    • Programming assignment 1.3 VS Code Power Moves
      • VS Live Share
      • VS IntelliSense
      • Matrix and vector manipulations
      • Programming fundamental concepts: Modules and Numpy
    • Workshop 1.3: Beam me up
      • Part 1: Solving an Initial Value Problem (Falling Head Test)
      • Part 2: Boundary Value Problem: Euler-Bernoulli Bending Beam
    • Group assignment 1.3: Rain, roots and runoff
      • Analysis
      • Report
  • Week 1.4
    • Programming assignment 1.4 Commit to clean data
      • Install GitHub Desktop
      • Make commit locally
      • Make commit online
      • Fetch and pull
      • Install git
      • Data cleaning
      • File import
      • Programming fundamental concepts: functions and matplotlib
    • Workshop 1.4: Fit happens
      • Fitting probability distributions
    • Group assignment 1.4
      • Analysis Wind Gusts
      • Report Wind Gusts Dataset
      • Analysis traffic dataset
      • Report Traffic Dataset
      • Analysis flow velocity dataset
      • Report Flow velocity Dataset
  • Week 1.5
    • Programming assignment 1.5 Git Happens
      • Branching and pull requests
      • Forking and pull requests
      • scipy.stats and 3D plots
    • Workshop 1.5: To Starve or Not to Starve
      • Bivariate Gaussian Distributions
    • Group Assignment 1.5. Gaussian & Furious
      • Analysis of Passing Maneuvers
      • Report
  • Week 1.6
    • Programming assignment 1.6 BotHeat.py
      • Python scripts in VS Code
        • script.py
        • my_first_script.py
      • Activate GitHub Copilot in VS Code
      • Programming a Thermostat with AI
        • main.py
        • ./controllers/__init__.py
        • ./controllers/onoff.py
        • ./controllers/predictive_onoff.py
        • ./plotting/__init__.py
        • ./plotting/plots.py
        • ./scenarios/__init__.py
        • ./scenarios/cold_morning.yaml
        • ./scenarios/door_open.yaml
        • ./scenarios/runner.py
        • ./scenarios/__init__.py
        • ./scenarios/filters.py
        • ./scenarios/temp_sensor.py
        • ./simulations/__init__.py
        • ./simulations/environment.py
        • ./simulations/room_model.py
        • ./tests/__init__.py
        • ./tests/test_onoff.py
        • ./tests/test_predictive_onoff.py
        • ./utils/__init__.py
        • ./utils/config.py
        • ./utils/rng.py
    • Workshop 1.6: Pipe Dreams
      • Mean and Variance Propagation
    • Group assignment 1.6: Icy Dicey Propagation
      • Propagation of Uncertainty
      • Report
  • Week 1.7
    • Programming Assignment 1.7: BugBuster
      • Setting Up Debugging in VS Code
      • Debugging a py file
        • debug_example.py
      • Debugging a Jupyter Notebook cell
      • Rubber Ducky Debugging
    • Workshop 1.7: Is it Melting?
      • Glacier Melting Model
    • Group Assignment week 1.7: I’m BLUE dabadidabada
      • Modelling surface uplift due to groundwater variations
      • Report
  • Week 1.8
    • Workshop 1.8: Water You Talking About
      • Non-Linear Water Model
    • Group assignment 1.8: Fit (and test) me baby, one more time
      • Non-linear Models
      • Report
  • Week 2.1
    • Programming Assignment 2.0: Q2 newbies
      • Show hidden files
      • Install TU Delft conda
      • Install VS Code
      • Setup mude-base environment
      • Execute python code in VS code in your mude-base environment.
      • GitHub account
      • Upload files to GitHub and check for pass
      • Report in a markdown file
      • Markdown in a Jupyter notebook file
      • Install GitHub Desktop
      • Make commit locally
      • Make commit online
      • Fetch and pull
      • Install git
      • Python scripts in VS Code
        • script.py
    • Programming Assignment 2.1: A Classy PDE
      • Functional programming
      • Object-oriented programming
    • Workshop 2.1: Go with the Flow
      • Propagation of a Cloud of Pollutant in River
    • Group assignment 2.1: simulation of transport of pollutant in rivers
      • Group assignment 2.1: simulation of transport of pollutant in rivers
      • Report
  • Week 2.2
    • Programming Assignment 2.2: SparseForge
      • Dense vs Sparse
    • Workshop 2.2: More Support
      • An Elastically Supported Rod
    • Group assignment 2.2: Flowing deeper underground
      • Finite Elements for Contaminant Transport
      • Report
  • Week 2.3
    • Programming assignment 2.3: PyOops
      • Iterable objects
      • Modulo
      • Stem plots
      • Errors
        • max_even_square.py
    • Workshop 2.3 You Try Meow (Miauw)
      • Discrete Fourier Transform (DFT)
    • Group assignment 2.3
      • Analyzing cantilever-beam accelerations and global Mean Sea-Level measurements
      • Report
      • Addition to GA 2.3
  • Week 2.4
    • Programming assignment 2.4: Axis of Awesome
      • 1. Numpy axis
      • 2. Statsmodels autocorrelation function
      • Assert Statements
      • Writing tests
        • ./max_even_squared.py
        • ./my_test.py
    • Workshop 2.4: Under Pressure
      • Time Series of Atmospheric Pressure
    • Group Assignment 2.4: The Memory Remains
      • Analysis of atmospheric temperature data
      • Report
  • Week 2.5
    • Programming assignment 2.5: From Code to Distributable
      • Packaging Your Python Code
    • Workshop 2.5: Profit vs Planet
      • Linear Programming in Python
    • Group assignment 2.5: Waterschap ‘dam
      • GA: Waterborne Urban Logistics in Amsterdam
      • MILP: Waterborne Urban Logistics in Amsterdam
      • Report
  • Week 2.6
    • Programming assignment 2.6: Split the party
      • Train/validation/test splits
        • ./split.py
    • Workshop 2.6: Fitting me softly
      • Your first neural networks
    • Group assignment 2.6: Rapture starts leaking
      • Neural networks for flood prediction
      • Report
  • Week 2.7
    • Programming assignment 2.7: Data Bears
      • Pandas
    • Workshop 2.7: Beyond the Mean of Green
      • Fitting extreme values
    • Group assignment 2.7: Torrential tales
      • Analysis
      • Report
  • Week 2.8
    • Workshop 2.8: Expensive Urn
      • Calculating insurance premiums
    • Group assignment 2.8: MUDE liberation day
      • Parametric distributions from empirical data
      • Report

Miscellaneous

  • Changelog
  • Credits and License
  • MUDE team
  • Repository
  • Open issue

Index

By MUDE Teachers and the Student Army from Delft University of Technology, built with TeachBooks and Jupyter Book, CC BY 4.0